UAE and Saudi Arabia prioritize investments in data streaming platforms to fuel AI

The UAE and Saudi Arabia are emerging as global frontrunners in the deployment of data streaming platforms, which are becoming a critical backbone for advancing national AI ambitions.

The 2026 Data Streaming Report from Confluent (an IBM company) reveals that 38% of organizations in the UAE and Saudi Arabia are already running agentic AI in production. This figure stands among the highest recorded globally, positioning the Gulf region as a leader in translating automation ambition into operational reality.

The report, which surveyed 4,600 technology leaders worldwide, indicates that Gulf organizations have identified exactly what is required to sustain this momentum. In both the UAE and Saudi Arabia, 95% of technology leaders believe that data streaming platforms can accelerate AI adoption. Additionally, 95% expect these platforms to increase the overall impact of their AI investments.

Data streaming platforms are systems that let organizations collect, process, and analyze data continuously in real time, rather than waiting for it to be stored and processed later in batches.

Strategic investment priorities

The strategic importance of data streaming platforms is evident in how regional leaders prioritize their spending. In both Gulf countries, the vast majority of respondents rank data streaming as a strategic business priority. In fact, they place it ahead of general AI and machine learning technologies, with 90% in the UAE and 88% in Saudi Arabia doing so.

Globally, data streaming platforms are rapidly shifting from emerging tools to enterprise imperatives. Across the entire survey pool, 88% of technology leaders rank these platforms as a high investment priority. The business returns justify the focus, with 50% of organizations reporting at least a fivefold return on investment and 88% achieving a twofold return or more.

Security and security management is the top investment focus for Middle Eastern companies when it comes to technology and innovation. This is no surprise as cyber attacks become more frequent and more damaging as hostile actors use AI and other emerging tools to craft increasingly dangerous attacks.

Overcoming infrastructure barriers

Despite rapid progress, GCC organizations remain realistic about the challenges ahead. Nearly three in four technology leaders in both markets report facing at least three major AI adoption barriers, mirroring global trends.

The three most common hurdles include insufficient infrastructure for real-time data processing, uncertainty around data lineage and quality, and a lack of specialized data skills. Furthermore, just over 66% identify data infrastructure as a specific bottleneck for agentic AI.

Rather than a sign of stalled progress, these findings reflect the practical realities of organizations that are already managing live production environments. To overcome these roadblocks, 95% of respondents in both markets look to data streaming platforms to make upstream data more trustworthy, contextualized, and discoverable.

“Most organizations do not have an AI investment problem, they have a data problem,” said Shaun Clowes, chief product officer at Confluent. “AI systems depend on fresh, accurate and contextual information, but too many are still being built on fragmented data, batch processes, and infrastructure that was not designed for continuous intelligence.”

The rise of data products

To scale these initiatives, organizations are moving toward modern data architectures. This includes a shift-left approach, which moves processing and policy enforcement closer to the original data source. Globally, 77% of technology leaders highlight extensive benefits from this method, up from 66% last year.

By cleaning and validating information early, companies can package data into reusable, governed data products. Technology leaders note that this strategy enables confident data sharing across business units and prevents errors from traveling downstream. As AI systems require cleaner information to avoid hallucinations, a real-time data foundation is becoming the primary differentiator for enterprise success.

“What the UAE and Saudi Arabia data tells us is genuinely encouraging,” said Karim Azar from Confluent. “These are markets that have moved decisively from AI experimentation into deployment, and their IT leaders have a clear view of what comes next. The focus on data streaming as a strategic priority reflects an understanding that sustaining AI performance at scale requires the right data infrastructure underneath it.”

“Backed by the commendable government investment and vision, I see the Middle East as well positioned to lead that next phase.”